fann_get_num_input
  • References/PHP/Function/Extensions/FANN/Fann

(PECL fann >= 1.0.0) Get the number of input neurons

2025-01-10 15:47:30
fann_set_cascade_weight_multiplier
  • References/PHP/Function/Extensions/FANN/Fann

(PECL fann >= 1.0.0) Sets the weight multiplier

2025-01-10 15:47:30
fann_get_rprop_decrease_factor
  • References/PHP/Function/Extensions/FANN/Fann

(PECL fann >= 1.0.0) Returns the increase factor used during RPROP training

2025-01-10 15:47:30
fann_get_quickprop_decay
  • References/PHP/Function/Extensions/FANN/Fann

(PECL fann >= 1.0.0) Returns the decay which is a factor that weights should decrease in each iteration during

2025-01-10 15:47:30
fann_get_learning_momentum
  • References/PHP/Function/Extensions/FANN/Fann

(PECL fann >= 1.0.0) Returns the learning momentum

2025-01-10 15:47:30
fann_create_shortcut
  • References/PHP/Function/Extensions/FANN/Fann

(PECL fann >= 1.0.0) Creates a standard backpropagation neural network which is not fully connectected and

2025-01-10 15:47:30
fann_train_epoch
  • References/PHP/Function/Extensions/FANN/Fann

(PECL fann >= 1.0.0) Train one epoch with a set of training data

2025-01-10 15:47:30
fann_create_sparse_array
  • References/PHP/Function/Extensions/FANN/Fann

(PECL fann >= 1.0.0) Creates a standard backpropagation neural network, which is not fully connected using

2025-01-10 15:47:30
fann_scale_train
  • References/PHP/Function/Extensions/FANN/Fann

(PECL fann >= 1.0.0) Scale input and output data based on previously calculated parameters

2025-01-10 15:47:30
fann_reset_MSE
  • References/PHP/Function/Extensions/FANN/Fann

(PECL fann >= 1.0.0) Resets the mean square error from the network

2025-01-10 15:47:30